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StephenBlackWasAlreadyTaken avatar StephenBlackWasAlreadyTaken commented on August 14, 2024

Im not super sure what you are refering too, if you want to paste your print line here I may be able to help more. But anticipate the raw value to bg conversion to be around ((raw/100)*1.05) - 28 or so, these numbers depend on the age of your sensor and the sensor itself, this is why a calibration algorithm is needed

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ijustlovemath avatar ijustlovemath commented on August 14, 2024

Those were the print lines! Just added a field, and put the actual value to
the left of the colon. Where did you get that fit? Where can I find the
calibration algorithm? Is it in the xDrip source?
On Monday, June 8, 2015, Stephen Black [email protected] wrote:

Im not super sure what you are refering too, if you want to paste your
print line here I may be able to help more. But anticipate the raw value to
bg conversion to be around ((raw/100)*1.05) - 28 or so, these numbers
depend on the age of your sensor and the sensor itself, this is why a
calibration algorithm is needed


Reply to this email directly or view it on GitHub
#34 (comment)
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StephenBlackWasAlreadyTaken avatar StephenBlackWasAlreadyTaken commented on August 14, 2024

xdrip has its own algorithm that can be found in the calibration model, its a weighted least squares linear regression (weights are age of calibration(linear but should be exponential in the future), sensor confidence(parabolic) and slope confidence(linear)), its split up using LaGrange interpolation because Its the only way I could figgure to write it out in java

https://github.com/StephenBlackWasAlreadyTaken/xDrip/blob/master/app/src/main/java/com/eveningoutpost/dexdrip/Models/Calibration.java#L394

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ijustlovemath avatar ijustlovemath commented on August 14, 2024

So raw/1000 is always used, but the coefficients (1.05 and -28) are calculated for the individual using least squares. It's usually a linear fit then? Or did you say exponential was better?

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ijustlovemath avatar ijustlovemath commented on August 14, 2024

Also, is the 1.05, -28 the inital approx, for low numbers of values?

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StephenBlackWasAlreadyTaken avatar StephenBlackWasAlreadyTaken commented on August 14, 2024

yeah I always divide by 1000 first to get the numbers more familiar, but you dont have to, you could just have your slope account for that.
I find there is some curvature at the higher end but its fairly linear, and yeah the 1.05 and the -28 are just rough approximations, a slope of around 1 is fairly common and -30ish seems to be the default intercept, though its not always a good fit, its a good way to estimate if you dont have any calibration data yet

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ijustlovemath avatar ijustlovemath commented on August 14, 2024

I can't believe I thought I would avoid using statistics in this project of mine :) Thanks, you've been helpful as always.

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